
. 
. encode country, gen(country_cat)

. 
. tab ethnocentrism

ethnocentri |
         sm |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |        184        0.90        0.90
      .0625 |        184        0.90        1.80
       .125 |        327        1.60        3.40
      .1875 |        436        2.13        5.53
        .25 |        984        4.81       10.34
      .3125 |      1,173        5.73       16.07
   .3333333 |          1        0.00       16.07
       .375 |      2,022        9.88       25.95
   .4166667 |         21        0.10       26.06
      .4375 |      2,026        9.90       35.96
         .5 |      3,906       19.09       55.05
      .5625 |      2,368       11.57       66.62
   .5833333 |          1        0.00       66.62
       .625 |      2,217       10.83       77.46
   .6666667 |         21        0.10       77.56
      .6875 |      1,411        6.90       84.45
        .75 |      1,437        7.02       91.48
      .8125 |        615        3.01       94.48
   .8333334 |         20        0.10       94.58
       .875 |        494        2.41       96.99
   .9166666 |         20        0.10       97.09
      .9375 |        268        1.31       98.40
          1 |        327        1.60      100.00
------------+-----------------------------------
      Total |     20,463      100.00

. gen ethno_factor = . 
(20,463 missing values generated)

. replace ethno_factor = 1 if ethnocentrism <=.375
(5,311 real changes made)

. replace ethno_factor = 2 if ethnocentrism >.375 & ethnocentrism < .625
(8,322 real changes made)

. replace ethno_factor = 3 if ethnocentrism >=.625 & ethnocentrism !=.
(6,830 real changes made)

. 
. tab ethno_factor

ethno_facto |
          r |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |      5,311       25.95       25.95
          2 |      8,322       40.67       66.62
          3 |      6,830       33.38      100.00
------------+-----------------------------------
      Total |     20,463      100.00

. 
. gen nonwhite = . 
(20,463 missing values generated)

. replace nonwhite = 1 if race != 1 & race != .
(6,925 real changes made)

. replace nonwhite = 0 if race == 1
(13,538 real changes made)

. 
. 
. *Model 1 
. 
. reg profile_chosen b4.country_cat i.mark_up_cat i.rating_cat, cluster(id)   

Linear regression                               Number of obs     =     19,910
                                                F(8, 995)         =     673.94
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2001
                                                Root MSE          =      .4473

                                                           (Std. Err. adjusted for 996 clusters in id)
------------------------------------------------------------------------------------------------------
                                     |               Robust
                      profile_chosen |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------------+----------------------------------------------------------------
                         country_cat |
A country outside the United States  |  -.1889865   .0103996   -18.17   0.000    -.2093942   -.1685788
                              China  |  -.3327845   .0117074   -28.43   0.000    -.3557585   -.3098104
                            Germany  |  -.1410494   .0102639   -13.74   0.000    -.1611908    -.120908
                                     |
                         mark_up_cat |
                                .25  |  -.1131769   .0091248   -12.40   0.000    -.1310829   -.0952709
                                 .5  |  -.2260483   .0099009   -22.83   0.000    -.2454774   -.2066192
                                  1  |  -.3639207   .0106709   -34.10   0.000    -.3848608   -.3429806
                                     |
                          rating_cat |
                   4 out of 5 stars  |   .1879173   .0090712    20.72   0.000     .1701165    .2057181
                   5 out of 5 stars  |   .3230192   .0096986    33.31   0.000     .3039871    .3420514
                                     |
                               _cons |   .6731111     .01122    59.99   0.000     .6510936    .6951287
------------------------------------------------------------------------------------------------------

. est store m1 

. 
. *Model 2 
. 
. reg profile_chosen b4.country_cat##i.ethno_factor i.mark_up_cat i.rating_cat, cluster(id)   

Linear regression                               Number of obs     =     19,910
                                                F(16, 995)        =     330.69
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2020
                                                Root MSE          =     .44684

                                                             (Std. Err. adjusted for 996 clusters in id)
--------------------------------------------------------------------------------------------------------
                                       |               Robust
                        profile_chosen |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------------+----------------------------------------------------------------
                           country_cat |
  A country outside the United States  |  -.1450109   .0182588    -7.94   0.000    -.1808411   -.1091807
                                China  |  -.2643402   .0213551   -12.38   0.000    -.3062465    -.222434
                              Germany  |  -.0936607    .019187    -4.88   0.000    -.1313123   -.0560092
                                       |
                          ethno_factor |
                                    2  |    .023198   .0165586     1.40   0.162    -.0092959    .0556919
                                    3  |   .0783205   .0172685     4.54   0.000     .0444336    .1122074
                                       |
              country_cat#ethno_factor |
A country outside the United States#2  |  -.0472972   .0247096    -1.91   0.056    -.0957861    .0011916
A country outside the United States#3  |  -.0741341    .026173    -2.83   0.005    -.1254947   -.0227734
                              China#2  |  -.0489927   .0283391    -1.73   0.084     -.104604    .0066186
                              China#3  |  -.1436718    .029272    -4.91   0.000    -.2011136   -.0862299
                            Germany#2  |  -.0301683   .0249387    -1.21   0.227    -.0791067    .0187701
                            Germany#3  |  -.1053659   .0263284    -4.00   0.000    -.1570315   -.0537003
                                       |
                           mark_up_cat |
                                  .25  |  -.1139668   .0091028   -12.52   0.000    -.1318296    -.096104
                                   .5  |  -.2261772   .0098886   -22.87   0.000     -.245582   -.2067724
                                    1  |  -.3644137   .0106639   -34.17   0.000      -.38534   -.3434874
                                       |
                            rating_cat |
                     4 out of 5 stars  |   .1875174   .0090368    20.75   0.000      .169784    .2052508
                     5 out of 5 stars  |   .3230585    .009657    33.45   0.000     .3041081    .3420089
                                       |
                                 _cons |   .6378839   .0150512    42.38   0.000     .6083481    .6674196
--------------------------------------------------------------------------------------------------------

. est store m2 

. 
. *Model 3 
. 
. reg profile_chosen b4.country_cat##i.ethno_factor i.mark_up_cat i.rating_cat i.pid3_lean age i.nonwhite i.college inc , cluster(id)   

Linear regression                               Number of obs     =     19,910
                                                F(22, 995)        =     242.20
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2020
                                                Root MSE          =      .4469

                                                             (Std. Err. adjusted for 996 clusters in id)
--------------------------------------------------------------------------------------------------------
                                       |               Robust
                        profile_chosen |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------------+----------------------------------------------------------------
                           country_cat |
  A country outside the United States  |  -.1450988   .0182684    -7.94   0.000    -.1809477   -.1092498
                                China  |  -.2646099   .0213621   -12.39   0.000      -.30653   -.2226899
                              Germany  |  -.0938996   .0191891    -4.89   0.000    -.1315554   -.0562437
                                       |
                          ethno_factor |
                                    2  |   .0232893   .0165447     1.41   0.160    -.0091771    .0557557
                                    3  |   .0783333   .0172735     4.53   0.000     .0444367      .11223
                                       |
              country_cat#ethno_factor |
A country outside the United States#2  |  -.0473093   .0247152    -1.91   0.056    -.0958093    .0011906
A country outside the United States#3  |  -.0739365   .0261743    -2.82   0.005    -.1252996   -.0225734
                              China#2  |  -.0487452   .0283479    -1.72   0.086    -.1043736    .0068833
                              China#3  |  -.1434068   .0292838    -4.90   0.000    -.2008719   -.0859417
                            Germany#2  |   -.030005   .0249467    -1.20   0.229    -.0789591    .0189491
                            Germany#3  |  -.1050644   .0263219    -3.99   0.000    -.1567173   -.0534116
                                       |
                           mark_up_cat |
                                  .25  |   -.114022   .0091009   -12.53   0.000    -.1318813   -.0961628
                                   .5  |  -.2262191   .0098913   -22.87   0.000    -.2456294   -.2068088
                                    1  |  -.3644692   .0106656   -34.17   0.000    -.3853988   -.3435395
                                       |
                            rating_cat |
                     4 out of 5 stars  |   .1875105   .0090313    20.76   0.000     .1697881     .205233
                     5 out of 5 stars  |    .323115   .0096593    33.45   0.000     .3041601      .34207
                                       |
                             pid3_lean |
                     Pure Independent  |  -.0049026   .0049305    -0.99   0.320     -.014578    .0047727
                           Republican  |  -.0014222   .0035499    -0.40   0.689    -.0083884     .005544
                                       |
                                   age |   .0000427   .0000991     0.43   0.667    -.0001518    .0002372
                            1.nonwhite |  -.0010469   .0036342    -0.29   0.773    -.0081784    .0060846
                             1.college |  -.0040733   .0033734    -1.21   0.228    -.0106931    .0025466
                                   inc |  -.0001436   .0004896    -0.29   0.769    -.0011043    .0008171
                                 _cons |   .6406411   .0155446    41.21   0.000     .6101372    .6711451
--------------------------------------------------------------------------------------------------------

. est store m3

. 
. 
. *Model 4 
. 
. reg profile_chosen b4.country_cat##i.ethno_factor i.mark_up_cat##i.ethno_factor i.rating_cat##i.ethno_factor i.pid3_lean age i.nonwhite i.college inc , cluster(id)   

Linear regression                               Number of obs     =     19,910
                                                F(32, 995)        =     179.66
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2037
                                                Root MSE          =     .44655

                                                             (Std. Err. adjusted for 996 clusters in id)
--------------------------------------------------------------------------------------------------------
                                       |               Robust
                        profile_chosen |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------------+----------------------------------------------------------------
                           country_cat |
  A country outside the United States  |  -.1455014   .0182098    -7.99   0.000    -.1812354   -.1097674
                                China  |  -.2648579   .0212718   -12.45   0.000    -.3066005   -.2231152
                              Germany  |  -.0943262    .019128    -4.93   0.000     -.131862   -.0567904
                                       |
                          ethno_factor |
                                    2  |    .040738   .0276263     1.47   0.141    -.0134745    .0949505
                                    3  |   .0903994   .0282917     3.20   0.001     .0348812    .1459177
                                       |
              country_cat#ethno_factor |
A country outside the United States#2  |  -.0470645   .0245793    -1.91   0.056    -.0952977    .0011687
A country outside the United States#3  |  -.0736368   .0261033    -2.82   0.005    -.1248606   -.0224131
                              China#2  |  -.0480178   .0282887    -1.70   0.090    -.1035301    .0074946
                              China#3  |  -.1439917   .0291976    -4.93   0.000    -.2012876   -.0866958
                            Germany#2  |  -.0295541   .0248841    -1.19   0.235    -.0783854    .0192772
                            Germany#3  |   -.104679   .0262931    -3.98   0.000    -.1562752   -.0530827
                                       |
                           mark_up_cat |
                                  .25  |  -.1030437   .0188051    -5.48   0.000    -.1399459   -.0661414
                                   .5  |  -.2258763   .0193293   -11.69   0.000    -.2638072   -.1879455
                                    1  |  -.3945602   .0205656   -19.19   0.000     -.434917   -.3542033
                                       |
              mark_up_cat#ethno_factor |
                                .25#2  |  -.0299175   .0230626    -1.30   0.195    -.0751745    .0153394
                                .25#3  |   .0049264   .0249048     0.20   0.843    -.0439457    .0537984
                                 .5#2  |  -.0305147   .0247544    -1.23   0.218    -.0790916    .0180622
                                 .5#3  |   .0360763   .0257434     1.40   0.161    -.0144414    .0865939
                                  1#2  |   .0133128   .0260271     0.51   0.609    -.0377615    .0643871
                                  1#3  |   .0745444   .0283431     2.63   0.009     .0189254    .1301635
                                       |
                            rating_cat |
                     4 out of 5 stars  |   .2000768   .0186969    10.70   0.000      .163387    .2367666
                     5 out of 5 stars  |   .3599095   .0190609    18.88   0.000     .3225054    .3973136
                                       |
               rating_cat#ethno_factor |
                   4 out of 5 stars#2  |   .0034251   .0234328     0.15   0.884    -.0425582    .0494084
                   4 out of 5 stars#3  |  -.0424739   .0238901    -1.78   0.076    -.0893546    .0044068
                   5 out of 5 stars#2  |   -.022906   .0244693    -0.94   0.349    -.0709233    .0251113
                   5 out of 5 stars#3  |  -.0828369   .0248889    -3.33   0.001    -.1316777   -.0339961
                                       |
                             pid3_lean |
                     Pure Independent  |  -.0049138    .005056    -0.97   0.331    -.0148354    .0050077
                           Republican  |  -.0014035   .0035335    -0.40   0.691    -.0083374    .0055304
                                       |
                                   age |   .0000611   .0001009     0.61   0.545    -.0001369    .0002591
                            1.nonwhite |  -.0006179   .0036561    -0.17   0.866    -.0077924    .0065566
                             1.college |  -.0044456   .0033952    -1.31   0.191    -.0111082     .002217
                                   inc |  -.0001896   .0004949    -0.38   0.702    -.0011608    .0007816
                                 _cons |   .6293716   .0213764    29.44   0.000     .5874236    .6713197
--------------------------------------------------------------------------------------------------------

. est store m4

. 
. 
. esttab m1 m2 m3 m4 using TableA4.csv, b(3) se(3) nobaselevels nogaps replace
(note: file TableA4.csv not found)
(output written to TableA4.csv)

. 
. 
. 